Attitude measurement using a single GPS receiver with two closely-spaced antennas

ABSTRACT

A system determines three-dimensional attitude of a moving platform using signals from two closely spaced Global Positioning System (GPS) antennas. The system includes three rate gyroscopes and three accelerometers rigidly mounted in a fixed relationship to the platform to aid in determining the attitude. The system applies signals from a first of the two GPS antennas to sufficient channels of a GPS receiver to support navigation. The system applies signals from a second of the two GPS antennas to the remaining receive channels, which are configured to support interferometry. The system optimally selects the navigation and interferometry channels to provide an interferometric heading solution. The system resolves the ambiguity normally associated with the interferometric heading solution by having the closely spaced GPS antennas and using interferometry to refine a coarse heading estimate from a GPS plus Inertial Measurement Unit (IMU) transfer alignment solution. The system achieves close sub-meter spacing of the two GPS antennas by merging many temporal interferometric measurements that result from an attitude memory provided by the IMU time-history solution.

RELATED APPLICATION(S)

This application claims the benefit of U.S. Provisional Application No.60/272,170, filed on Feb. 28, 2001; the entire teachings of which areincorporated herein by reference.

GOVERNMENT SUPPORT

The invention was supported, in whole or in part, by contractsDAAB07-00-C-J603 and DAAB07-01-C-J403 from US Army CommunicationsElectronics Command. The Government has certain rights in the invention.

BACKGROUND OF THE INVENTION

The present invention relates to moving platforms, specifically, to asystem for determining the geodetic attitude of an arbitrarily movingplatform. Moving platforms include vehicles, such as aircraft, groundvehicles, boats or spacecraft or equipment mounted to vehicles that canbe reoriented relative to the vehicle body. The platforms may betraveling at fast or slow speeds, may be maneuvering or non-maneuvering,and may be occasionally stationary relative to geodetic space. Theseplatforms require knowledge of their geodetic attitude in order, forexample, (i) to support safety or stability control systems, (ii) topoint an antenna or sensor boresight at a geodetically known target,(iii) to control their geodetic position or attitude movement, or (iv)to register the information sensed along the boresight onto a mapprojection with geodetic coordinates. The sensor or antenna boresight isthe centerline of some signal collection or signal transmissionaperture.

Earth-rate sensing through gyrocompassing, GPS interferometry, andtransfer alignment (TA) are possible implementation approaches forprecision geodetic orientation measurement systems for arbitrary movingplatforms. Each technique is in widespread use, but each technique alonehas significant limitations for precision pointing.

Earth rate sensing requires the use of a gyroscope with accuracy muchbetter than the earth's 15-deg/hr-rotation rate. The gyroscopes used forconventional gyrocompass systems have drift specifications of less than0.1 deg/hr. Modern military gyroscopes, currently used on missiles, canachieve a 1 deg/hr accuracy with prices of about $5000 in largequantities. For a 1-deg/hr tactical weapon grade gyroscope, the northseeking accuracy is about 4 deg and is not sufficiently accurate forbroadband pointing.

GPS interferometry measures GPS carrier phase to GPS satellites frommultiple spaced antennas. Carrier phase differencing removes all commonmode ionospheric corruption from the differenced signals. The remainingphase difference can be used to infer range to GPS satellites tomillimeter (mm) accuracy. The measurement is corrupted by cable-inducedphase differences, on-vehicle multipath, and a whole-cycle GPSwavelength ambiguity that is 19 cm for commercial GPS. A method notbased on interferometry is often used to get close to the correctattitude and reduce whole-cycle ambiguity. Commercial motioncharacterization systems that use GPS interferometry are available, butimpose installation difficulties by requiring multiple antennasdispersed over several square meters. Also, the lack of wide-bandwidthattitude memory prevents any accuracy enhancement through data averagingunless the system is perfectly stationary.

Transfer alignment is the most widely used precision orientationmeasurement method for military applications. Transfer alignmentsynergistically combines an Inertial Navigation System (INS) withsingle-antenna GPS system to estimate position and attitude. The INS,traditionally used only in military applications and high-end aircraft,has an internal instrument suite that provides measurement of three axesof acceleration and three axes of rotation rate. Mathematicalmanipulation of the acceleration and rotation rate measurements providesthe position, velocity, and attitude of the platform at a highbandwidth. However, the navigation solution will drift unless someexternal corrections are incorporated. For low cost inertial components,the drift will occur rapidly. GPS external measurement is most oftenused for the INS corrections. For GPS transfer alignment, INS-derivedvelocity and GPS-derived velocity are differenced, and the time-historyof the differences is then used to infer errors in assumed geodeticalignment of the INS axes. The need to maintain persistent changingvelocity to enable attitude measurement and the traditional high cost ofthe INS make TA unsuitable for most commercial applications. TA uses amathematics model where attitude errors propagate into the IMU-derivedplatform position and velocity in geodetic coordinates. By independentlymeasuring the geodetic position and velocity with the navigation GPSsolution, the attitude errors are observed and corrected. However, theattitude errors are observable through the velocity, such that a changein attitude produces a change in geodetic velocity. The presence of aspecific force acting on the platform must be present to impart attitudeobservability. A specific force is almost always present in the verticaldirection since a force must be imposed to maintain the platform fromfalling towards the center of the earth. Thus, attitude orthogonal tothe vertical direction, the platform roll and pitch angles, are readilyobserved for any platform not in a free-fall condition. However, aplatform at a constant velocity in the horizontal plane will have noobservability of attitude about the vertical direction, the platform yawangle. For successful transfer alignment, the horizontal plane motionmust be sensed by the GPS carrier phase measurements from the navigationGPS antenna. Because integrated carrier phase measurements are accurateto millimeter (mm) levels, even for a very low cost commercial receiver,only a slight platform motion is sufficient for some level of headingattitude measurement. Most moving platforms will have some motion fromexternal disturbances for attitude estimation to an accuracy of severaldegrees.

In addition to the techniques just described, the prior art alsoincludes patents teaching techniques to determine geodetic attitude frommoving vehicles. For example, U.S. Pat. No. 5,575,316 to Buchlerdescribes a generalized motion characterization system employingmultiple GPS antennas and receivers and an IMU device. Key to Buchler'spreferred embodiment of this device, and clearly stated throughout hissample embodiment and claims, is a requirement to overcome a largeuncertainty in the initial platform heading. This initial heading error,coupled with a 1 m GPS antenna spacing, causes the GPS interferometricrange-to-satellite ambiguities to produce ambiguous platform headingmeasurements. The large initial heading error of 10 deg stated byBuchler results from the use of gyrocompassing to ascertain initialplatform heading independent of GPS interferometry. Gyrocompassing, asis understood in the art, relates to sensing the rotation rate of the15-deg/hour-earth vector. The LN-200 IMU rate gyro employed in theBuchler invention has a gyro drift of 1 deg/hr that produces the 10 degheading error following a gyrocompass event. The majority of the Buchlerinvention relates to the refinement of the initial attitude uncertaintyto a level where no ambiguities are present in the final measurement.

The Buchler invention poses at least six considerations that prevent lowmanufacturing cost, ease of installation, and operation with arbitraryplatforms:

Two independent GPS receivers are required to determine doubledifference relationships used for the interferometric processing. Thismeans that two oscillators are used in the GPS RF front-enddownconversion process. The use of two oscillators causes addedmeasurement noise when carrier phase from the two channels aredifferenced. Also, the use of two independent GPS receivers increasesthe cost.

The use of a 1 deg/hr IMU, necessary for gyrocompassing attitudeinitialization, demands a relatively high-cost IMU unsuitable for mostcommercial applications.

The use of a gyrocompass stage to initiate the attitude measurementprocess is not suitable for arbitrary platform operations.Gyrocompassing restricts the platform motion and requires a significantperiod of initialization time.

The Buchler invention assumes the use of a barometric altimeter forindependent altitude measurement. Such a measurement is problematic forall platforms because of the need to maintain a clean and preciselyoriented passage to ambient airflow.

The Buchler invention assumes that all GPS satellites visible on oneantenna are also visible to the second antenna to arrive at the doubledifferences used by a Kalman filter. This suggests a requirement for useof either two standard GPS receivers, each tracking the same GPSsatellites, or specialized, more costly, receiver architecture withtwice the standard number of channels.

A problem is posed by the Buchler invention that relates to achievableaccuracy of the attitude solution. The bulk of the embodiment relates tothe use of a double-difference phase function, which Buchler claims totreat as a scalar measurement to the Kalman filter. Double differencesresult in M-1 scalar measurements for M GPS satellites being tracked.However, the measurements are correlated because common GPS satelliteranges are used in multiple measurements. Treating such correlatedmeasurements as uncorrelated scalar measurements by the Kalman filterleads to a suboptimal filter, as is well known in the art. Theembodiment mentions the use of a single-difference measurementformulation but does not describe how this mechanization will produceuncorrelated scalar measurements for the Kalman filter.

In another patent example, U.S. Pat. No. 5,617,317 to Ignagai describesa generalized motion characterization system employing multiple GPSantennas and receivers and an IMU device. The Ignagai invention assumesthe existence of a separate Inertial Sensor System on the platform,distinct from the dual-antenna GPS system. Ignagai does not fullyintegrate the IMU rotation rate and acceleration measurements into theattitude measurement processing; instead, the Ignagai invention takesindependently derived attitude information from the Inertial SensorSystem and combines it with differential range information determinedfrom a two-antenna interferometric GPS system. Ignagai uses a simplethree-state Kalman filter to smooth the angular misalignment between thetwo independently derived heading angles. As in the Buchler invention,two independent GPS antenna/receivers are used coupled to a differentialrange processor. The Inertial Sensor System is said to be an Attitudeand Heading Reference System (AHRS), which is known with the art to be aself-contained navigation system employing a separate air-data system,as explained by Ignagai.

Ignagai describes three types of interferometric measurement processing:differential range, differential carrier phase, and differentialintegrated Doppler counts. Ignagai discusses antenna separations of10-20 m for the differential range measurement, 1-2 m for the integratedDoppler count method, and “a possibility” of 3.75 inches separation forthe differential carrier phase measurement. However, the embodimentdevelops only the formulations for the differential range and theintegrated Doppler count methods. Ignagai makes little mention of theinterferometric heading ambiguity problem treated extensively byBuchler.

Ignagai discusses the heading initialization as using the aircraftcockpit magnetic compass for a stationary aircraft, or by using theaircraft track heading while the aircraft is taxiing on the ground. Theaircraft track heading initialization process assumes that the IMU andantenna baseline are aligned with the taxi velocity so that the headingalignment is equal to the ground velocity vector as measured from GPS.Ignagai notes that this is problematic for an in-air initialization ofthe heading because the aircraft body attitude is not aligned with thevelocity vector.

Seven considerations are posed by Ignagai that prevent achieving lowmanufacturing cost, ease of installation, and ease of operation witharbitrary platforms:

Two independent GPS receivers are required to determine theinterferometric relationships used for the interferometric processing.This means that two oscillators are used in the GPS RF front-enddownconversion process that contributes to the phase measurement noise.Also, two GPS receivers increase the cost.

Ignagai assumes a separate and distinct Inertial Sensor System, such asan AHRS, that will be too costly for general commercial applications.

The use of an aircraft track heading procedure for initializing theheading measurement process is not generally suitable for platformswhere the IMU and GPS baseline are arbitrarily oriented with respect tothe platform velocity vector.

Ignagai assumes the use of an Air Data Sensor. Such a measurement sensoris problematic for all platforms because of the need to maintain a cleanand precisely oriented passage to the ambient airflow.

Ignagai assumes that all GPS satellites visible to one antenna are alsovisible to the second antenna to arrive at the interferometricdifferences used by the Kalman filter. This suggests the requirement foreither using two standard GPS receivers that each tracks the same GPSsatellites or using a tailored receiver architecture with twice thestandard number of channels.

Ignagai uses a simple three-state Kalman filter for smoothing theinertial sensor and GPS interferometric angle errors. Such a simplisticfilter form cannot exactly represent the precision attitude memoryachievable when a more complete IMU and GPS integration is mechanized.This prevents the optimal merging of past interferometric measurementsand restricts the achievable measurement accuracy.

Ignagai integrates the Inertial Sensor System and interferometric rangesystem through a filter applied to a Euler angle. This approach resultsin a mathematical problem as the system crosses the earth poles. Acoordinate system switch is required as the platform reaches higherlatitudes. This is undesirable and reduces the generality of theinvention for general platform geodetic motion.

Two more patent examples include U.S. Pat. No. 5,672,872 to Yeong-Weiand U.S. Pat. No. 5,809,457 to Yee. Both Yeong-Wei and Yee describe ageneralized motion characterization system employing a GPS antenna andreceiver integrated to an IMU device via a Kalman filter. Both Yeong-Weiand Yee inventions use a single GPS antenna rather than the dualantennas of the Buchler and Ignagai inventions. Yeong-Wei specificallydescribes the well-known problem of such single-GPS-antennamechanizations: persistent maneuvers are required to enable the headingattitude to be observable. Purposeful aircraft maneuvers are describedas necessary for the example aircraft embodiment. Yee is specialized toan application where the GPS antenna and IMU are located to theboresight of a sensor or antenna system. However, Yee makes no referenceto the problem of heading errors when persistent horizontal planemaneuvers are not present. Yee makes no mention of intentional maneuversfor achieving the heading alignment. Neither Yeong-Wei nor Yee mentionsthe use of dual GPS antennas for the purpose of avoiding the headingdrift when horizontal plane motion is not present.

SUMMARY OF THE INVENTION

Numerous commercial applications demand the pointing of a sensorboresight towards a location known in geodetic coordinates. Someemerging applications include pointing a highly directional antenna atan orbiting broadband satellite or pointing a sensor at a pre-determinedground location from an aircraft or ground vehicle and controlling thethrottle, braking, and suspension systems to insure safety andstabilization of automobiles. Many other applications exist that requirethe attitude of a platform structure to permit maneuvering in geodeticspace, such as the control of an aircraft in flight. Finally, manyapplications exist where the boresight of a sensor is required to beknown, but not controlled, for the purpose of geo-registering theinformation received by the sensor. This is the case, for example,during the collection of image sequences that are to be used forreconstruction of objects observed within the images or for mosaicking asequence of images onto a common map coordinate system.

The prior art provides approaches to the commercial requirements;however, each of the prior art approaches must be tailored to thespecific platforms, requires costly hardware components and/orinstallation techniques, imposes maneuver restrictions on the platforms,and does not take full advantage of the available GPS and IMUmeasurements.

The present invention provides a complete six-degree of freedom geodeticcharacterization of an arbitrary dynamic or stationary platform. Thegeodetic characterization includes position, velocity, acceleration,attitude and attitude rates. The present invention poses no restrictionon the motion of the platform and requires no electrical connectivity tothe platform except for power. Furthermore, systems employing theprinciples of the present invention can be both manufactured andinstalled at costs significantly less than systems defined in the priorart.

One embodiment of the present invention includes two navigation GPSantennas, three rate gyroscopes, three accelerometers, and at least oneprocessor to calculate the geodetic characterization of the platform.The processor(s) determine an integrated navigation solution throughsignals received by the navigation GPS antennas and through signalsderived by the gyroscopes and accelerometers.

In the process of determining a navigation solution, the navigation GPSantennas, preferably electrically similar, feed received RF signals totwo RF downconverters. Both RF downconverters utilize the same thermallycontrolled oscillator so that any oscillator-induced noise iscommon-mode between the two RF front-end channels. Signals output by thedownconverters go into a single, commercially available, 12-channel,correlator chip that tracks pseudorandom noise signals from up to twelveGPS satellites and outputs channel tracking information, which is aninput to the processor(s).

The processor(s) use the channel tracking information to determine thetime-of-transit for each GPS signal from its respective GPS satellite.Each time-of-transit has a common-mode bias due to the processor clockerror. The processor(s) control the GPS satellite signal trackingprocess for each channel and decode the digital messages also containedin the GPS satellite signals. If four GPS satellites are tracked, thenthe processor(s) determine the common mode clock bias and the geodeticposition of the platform using methods well known in the art.

The processor(s) also accept data from the six IMU sensors: the threerate gyroscopes mounted along orthogonal axes and the threeaccelerometers mounted collinearly with the gyroscope axes. The rotationrate and acceleration data provided by the gyroscopes andaccelerometers, respectively, are used by the processor(s) to form astrapdown navigation solution using methods that are well known in theart. The strapdown navigation solution results in a position, velocity,and attitude geodetic navigation solution. The processor(s) use awell-known transfer alignment procedure to determine the completethree-dimensional attitude of the platform by comparing the strapdownnavigation solution with the navigation solution derived solely from thenavigation GPS antennas, as described above. The processor(s) are ableto provide the geodetic characterization of the platform using rategyroscopes providing poorer than ten degrees/hour accuracy underarbitrary motion conditions. The principles of the present inventioninclude at least five innovations:

Utilization of available spare capacity within commercially availablelow cost GPS receivers enables GPS interferometry using only a singleGPS receiver. This provides both cost advantages and accuracyimprovement because the same oscillator is used for downconversion ofboth GPS antenna signals.

Close spacing of two GPS antennas, down to about 3 inches, depending onaccuracy requirements of the application. This enables simplifiedpackaging, with less space involvement, and installation to the mobileplatforms. Close antenna spacing also minimizes the effects of multipathinterference on the attitude solution.

Tight integration of the single-GPS-antenna transfer alignment processwith the dual-antenna GPS interferometry process. This yields headingestimation independent of the GPS interferometry solution so thatheading ambiguities normally resulting from interferometric solutionsalone are immediately resolved. This obviates the requirements forheading initialization procedures such as gyrocompassing,alignment-to-velocity, or use of a magnetic compass from movingplatforms. For a stationary platform, integration with the IMU enables asimple method for resolving the heading ambiguities normally plaguingGPS-only attitude measurement methods.

Use of single-difference GPS carrier phase measurements. This ensuresthat uncorrelated scalar measurements are provided to a Kalman filter asis required for optimal estimation. This enables improved measurementaccuracy over scalar double-difference measurements that arefundamentally correlated.

Acceleration aiding of the GPS receiver channels from the IMUinformation. This allows tightening the channel track loop bandwidths bypredicting platform velocity providing added multipath resistance overclose antenna spacing and the narrow correlator technologies well knownin the art.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a pictorial diagram of an example broadband communicationscenario that is enabled by an motion characterization system that isdeveloped according to the principles of the present invention;

FIG. 2 is a high-level block diagram of the measurement and processingcomponents of the motion characterization system of FIG. 1;

FIG. 3 is an electromechanical schematic diagram showing the centralconcept underlying GPS interferometry used by the motioncharacterization system of FIG. 1;

FIG. 4 is a block diagram of an example implementation of the motioncharacterization system of FIG. 2 having an Inertial Measurement Unit(IMU) and a GPS receiver with an integrated Digital Signal Processor(DSP);

FIG. 5 is a schematic diagram depicting a preferred embodiment of themotion characterization system in FIG. 4 and showing the segmentation ofnavigation signals to support processing into navigation channels andinterferometry channels;

FIG. 6 is a vector diagram showing the measurement of three axes ofacceleration and three axes of attitude rate by the IMU in FIG. 5 afterthe calibration of the IMU to align the axes;

FIG. 7 is a schematic diagram of the IMU of FIG. 5 and shows theintegration of three accelerometers, three gyroscopes, and amicroconverter for analog-to-digital conversion and processing;

FIG. 8 is a flow diagram for the DSP-based GPS receiver of FIG. 5 andshows the selection and allocation of navigation signal channels, theuse of navigation and interferometry correlators, the aided measurementof system parameters, and the use of a Kalman Filter navigator toprovide a navigation solution, clock corrections, aiding information,and channel allocation information;

FIG. 9 is an antenna beam diagram showing the characteristics ofbroadband communication at high frequencies that pose fundamentalrequirements on attitude measurement accuracy;

FIG. 10 is a plot produced by a system simulation for the motioncharacterization system modeled in the block diagram of FIG. 5, whereattitude measurement error is parameterized by antenna baseline length;

FIG. 11 is another plot produced by the system simulation for the motioncharacterization system modeled in the block diagram of FIG. 5, whereattitude measurement error is parameterized by gyroscope error; and

FIG. 12 is a block diagram that shows the integration of the motioncharacterization system into a broadband communication system.

The foregoing and other objects, features and advantages of theinvention will be apparent from the following more particulardescription of preferred embodiments of the invention, as illustrated inthe accompanying drawings in which like reference characters refer tothe same parts throughout the different views. The drawings are notnecessarily to scale, emphasis instead being placed upon illustratingthe principles of the invention.

DETAILED DESCRIPTION OF THE INVENTION

A description of preferred embodiments of the invention follows.

The current explosive growth in mobile vehicle display products isaccompanied by increased demand for robust access to high-qualityspatial information and to broadband data sources, such as streamingvideo, digital television, and high definition television (HDTV). Thepresent invention can be used to facilitate delivery of multimediabroadband data to users in vehicles, such as cars, planes, trains,boats, and airplanes. New generations of satellite-based broadbanddelivery systems use Low Earth Orbit (LEO) satellites operating at 20GHz or higher frequencies and require precise pointing of highlydirectional antennas to achieve high data rates.

The present invention permits use of poor performance, low-cost motionsensing devices both to enable accurate, affordable, antenna pointingsolutions for broadband mobile communications and to permit the robustdelivery of spatial information to both military and commercialplatforms. These new delivery systems place stringent requirements onthe user equipment for antenna pointing accuracy, operation in adversemultipath environments, satellite tracking performance, andcommunication effectiveness to achieve continuous operation. Userequipment for fixed terminals can use traditional mechanical antennaapproaches. User equipment for mobile vehicles, however, demands moreinnovative solutions to meet requirements for unobtrusive surfacemounting, high pointing accuracy from a high-dynamics moving platform,and low satellite-to-satellite switching times.

FIG. 1 is a pictorial diagram of an example application that may employthe present invention. The example application is a mobilecommunications system that provides, for example, video content to amoving vehicle 3. The vehicle 3 is equipped with an antenna 1 that iscapable of steering a beam 2 at a broadband, content-delivery satellite4 providing the video content. The antenna 1 has an integrated geodeticmotion characterization system (shown in FIG. 2), employing theprinciples of the present invention, that uses navigation carriersignals from the Global Positioning System (GPS) satellites and motionsignals from motion sensing devices (shown in FIG. 2) to calculate roll,pitch, and yaw angles of the vehicle 3. The antenna 1 uses these angles,or beam angle control signals calculated therefrom, to keep the beam 2pointing at the content-delivery satellite 4. Keeping the beam 2pointing at the content-delivery satellite 4 results in good signalquality of the video signal displayed in a display 5 viewed bypassengers in the vehicle 3.

The present invention also provides characterizations of vehicle motionthat can be applied to improved vehicle safety systems, enhancements inoccupant convenience, evolutionary development of telematics andcommunications systems, and delivery of data to improved vehicledisplays. Further, the present invention provides an innovative,low-cost measurement solution that allows consolidation of discreteelements and the synergistic combination of hardware and softwaresystems.

Table 1 is a chart detailing vehicle systems for safety and broadbandaccess, with the associated components and sensors listed in thedecision support and principal sensors columns, respectively. Thecomments column includes a list of example applications and uses.

TABLE 1 Vehicle Decision Principal System Support Sensors CommentsSafety Brake Integrated Unintended change in modulation, gyroscopes,direction or orientation; steering accelerometers, excessive rollsystem, and GPS Road condition monitoring suspension, Telematics supportand engine Vibration signature control Stabilized Road lane surveillancecamera and Collision avoidance and pre- radar crash recognitionBroadband Antenna Integrated Satellite-based and tower- Access pointinggyroscopes, based communications for accelerometers, high data rateinformation and GPS

FIG. 2 is a schematic diagram of an embodiment of the motioncharacterization system 6 employing the principles of the presentinvention that can be integrated into the antenna 1 of FIG. 1 orapplications listed in Table 1. The motion characterization system 6includes two antennas 7, motion sensing devices 8, and at least oneprocessor 9. The antennas 7 and motion sensing devices 8 are rigidlyconnected, directly or indirectly, to the body or platform, such as avehicle rooftop, whose angular attitude is being sensed.

The motion characterization system 6 uses the two antennas 7 to receivenavigation signals, the motion sensing devices 8 to provide informationabout body motion, and the processor 9 to estimate the motion of thebody for delivery to other system applications. The navigation signalsmay be transmitted by GPS, GLONASS, Galileo, the Global NavigationSatellite System (GNSS), or other navigation systems as available. Themotion sensing devices 8 may include gyroscopes, accelerometers,magnetometers, tilt meters, speed measurement devices, navigationreceivers, or other sensors. The processor 9 may be a general-purposecomputer, digital signal processor (DSP), application specificintegrated circuit (ASIC), or other computing device. The preferredembodiment uses minimal number of motions sensing devices to achieveperformance objectives, but can be extended to include additional motionsensing devices and other sensors to improve effectiveness or extend thenumber of simultaneously supported applications.

The processor 9 uses the GPS signals and motion measurements to achievesufficient motion estimation accuracy for the pointing, safety,telematics, and control applications. Navigation systems, such as GPS,provide precision positioning at all earth locations, at commoditypricing that is typically less than $50 for commercial applications. GPShowever, does not provide attitude information. Therefore, the motioncharacterization system 6 determines both the orientation and change oforientation of the receiving platform by other techniques. The motioncharacterization system 6 measures attitude, as parameterized by roll,pitch, and yaw, under all motion conditions, including the difficultsituation of no motion.

When the platform is nominally horizontal, to within +/−30 deg, and theplatform is stationary or moving at walking-to-driving speeds, neithermagnetic compass nor accelerometer-alone tilt sensors are sufficient forthe approximately 0.5 deg geodetic attitude measurement accuracyrequired for broadband mobile communication. Magnetic compass solutionsare sensitive to local magnetic disturbances, and accelerometer-onlysolutions are sensitive to platform lateral accelerations.

Although Earth-rate sensing through gyrocompassing, GPS interferometry,and transfer alignment (TA) are possible implementation approaches, thelimitations associated with these approaches makes them unsuitable foran application such as content delivery to mobile communicationssystems. For example, the problems associated with TA stem from theinability to sense yaw attitude directly. TA requires changes in vehiclevelocity to enable estimation of yaw from velocity matching and requiresprecision gyroscopes because of the algorithmic need for heavy smoothingof the platform motion. The present invention overcomes this dilemma bysensing the yaw attitude from a completely different source—dual antennainterferometry. Thus, the motion characterization system 6 combines TAwith dual antenna interferometry to achieve the approximate 0.5 degreegeodetic attitude measurement accuracy required for the broadband mobilecommunication system and other applications.

FIG. 3 is a high level schematic diagram of dual antenna interferometryas used by the motion characterization system 6, and consists of GPSantennas 7, associated receiver channels 10, and a range differencecalculation unit 11 encapsulating inertial measurement, signalprocessing, and estimation functions. The difference calculation unit 11provides signal phase measurements that are accurate to millimeterprecision after GPS interferometry. The geodetic attitude is calculatedas sin (θ)=ΔR/L, where ΔR is the difference in GPS signal phase and L isthe antenna baseline length.

FIG. 4 is an embodiment of the motion characterization system 6including the two antennas 7 and one or more substrates containing themotion sensing devices 8, processor(s) 9, and other interfacecomponents. In one embodiment, the processor(s) 9 include a DSP-basedGPS receiver 12 with excess capacity to support the GPS, navigation,interferometry, and control calculations. Additional processors may berequired for some complicated control applications and may be programmedto operate in a parallel manner. In one embodiment, the motion sensingdevices 9 include an Inertial Measurement Unit (IMU) 13 to provide themotion measurements of the platform or body.

The motion characterization system 6 provides acceptable performance forhigh data rate broadband applications while permitting use of poorquality Micro Electromechanical System (MEMS) devices in the IMU 13 anda commodity-priced DSP-based GPS receiver 12 for the processor 8. Betterquality devices will lead to more accurate attitude measurement;however, with only poor quality MEMS devices (e.g., rate gyroscopeshaving poorer than 10 degrees/hr accuracy), the motion characterizationsystem 6 achieves the less than 1-degree attitude measurement accuracyrequired for high data rate, broadband communications with LEOsatellites at Ka band.

The motion characterization system 6 requires only two antennas becauseTA provides precision estimates of roll and pitch. In addition, aheading solution provided by the motion characterization system 6 isrelatively insensitive to GPS antenna spacing because of the smoothingbenefits of even low-accuracy inertial components. While considerableeffort has gone into optimizing techniques for GPS interferometry andTA, no commercially available systems rely on the integration of thetwo. The result is the motion characterization system 6 having anelegant implementation of a simple electronics architecture that can bepopulated with a handful of breakthrough technology chips and/orcomponents.

When the platform is stationary, the processing accurately measures theroll and pitch attitude relative to the local vertical from themeasurements provided by the motion sensing devices. The processor 9uses the differential carrier phase measurement from GPS interferometryto determine yaw; however, the yaw estimate from a single GPS satelliteis ambiguous due to the 0.19 m GPS wavelength. When the navigation andinterferometry GPS antennas track multiple GPS satellites, an algorithmresolves the interferometric ambiguity in yaw.

The GPS receiver 12 may be a modem GPS receiver that uses twelvecorrelator channels to search the complete range-Doppler space for GPSnavigation signals, reducing the time-to-first-fix (TTFF) and enablingrapid initialization of the position solution on startup or followingloss of GPS satellite lock. However, the number of visible GPSsatellites is very rarely over nine, and frequently only five to seven;thus, the GPS receiver 12 nearly always has access to spare correlatorchannels after initialization. In addition, performance improves onlymarginally when over six GPS satellites contribute to the solution.Thus, once several GPS satellites are acquired, four to five of thecorrelator channels are unused, and the motion characterization system 6uses the spare channels for interferometry. The traditionalinterferometric solutions have multiple parallel receivers that eachtrack the same GPS satellites. For example, the common implementation ofa conventional GPS receiver has twenty-four correlator channels so thatsix GPS satellites from those in view can be tracked on each of fourantennas.

GPS receivers are often mechanized with a single radio frequency (RF)front end and a 12-channel correlator. The RF front end converts theinput GPS RF signal from an associated antenna to a digital intermediatefrequency (IF) signal that is then fed into each of the identical twelvechannels of the correlator chip for tracking up to twelve GPSsatellites.

FIG. 5 is a preferred embodiment of the motion characterization system 6using navigation signal antennas 7, two low noise amplifiers (LNAs) 14to establish correct signal levels, and two RF front ends 21, which aredriven by a common oscillator 16 to reduce system noise figure.

The motion characterization system 6 uses one of the two GPS antennas 7as a navigation GPS antenna, feeding RF signals to a set of navigationchannels 17, which permits the receiver 15 to use a GPS satelliteacquisition process that is identical to the conventional GPS receiver.Typically, the correlator channels in the DSP-based GPS receiver 15 usea fast acquisition process on as many available channels as necessary toprocess signals from all GPS satellites in view. The motioncharacterization system 6 produces a complete geodetic position andvelocity solution. When combined with the data from the IMU 13, thissolution also gives excellent roll and pitch attitude, and good headinginformation when the platform is persistently maneuvering in thehorizontal plane. Without such persistent maneuvers or when the platformis stationary, poor heading measurements result with only usingnavigation channels.

Following initialization, the motion characterization system 6 uses thesecond of the GPS antennas 7 as an interferometry antenna, which feedsRF signals to the remaining GPS receiver channels, referred to asinterferometry channels 18. Through interferometric range measurement,the GPS satellites provide information on the vehicle heading relativeto north for augmenting the heading information provided by the IMU 13and navigation antenna alone. The IMU 13 and navigation antenna providesufficient information to allow excellent roll and pitch attitudeinformation.

The preferred embodiment uses a single GPS receiver to achieve reducedGPS phase measurement errors because the common oscillator 16 is usedfor both antenna paths. Also, platform heading is known to an accuracyof 1-2 deg, independent of the two-antenna interferometric process,through the single-antenna-plus-IMU solution with an optional magneticcompass. The accurate heading combined with close GPS antenna spacingenables a unique interferometric solution for the heading as refinedthrough the interferometric process.

GPS interferometry that uses three or four antennas can achievethree-dimensional attitude measurement without inertial aiding, butrequires antenna spacing on the order of 1 meter to achieve sufficientaccuracy. A single GPS antenna and receiver when combined with anInertial Measurement Unit (IMU) that includes three rate gyroscopes andthree accelerometers can also achieve three-dimensional attitudemeasurement. However, this device requires lateral maneuvers of theplatform so that velocity matching between the GPS and inertialsensor-derived velocity solutions can occur. The present invention,however, uses two closely spaced GPS antennas combined with an IMU toprovide high accuracy for both stationary and moving vehicles.

Because the motion characterization system 6 uses two antennas 6 thatcan be spaced as closely as three inches apart, typical installationcosts on the platforms are reduced. Also, though many embodiments arepossible, a single embodiment of the invention is suitable for allcandidate air, space, ground, and sea platforms with minimummodification. The antennas used on a platform are preferably compact andvery closely spaced so that only a single compact, flush-mount componentis mounted to the upper surface of the platform. Also, in oneembodiment, no external equipment is required to be on the platform forgenerating the measurement other than a power source.

Alternative embodiments may use a different oscillator for each RF frontend, a DSP-based GPS receiver for navigation functions and a separateDSP-based GPS receiver for interferometry functions, a GPS receiver anda separate DSP for processing functions, and other architecturalcombinations. The preferred embodiment is simple, and leads to a lowcost, high performance solution. The DSP-based GPS receiver 12 alsoprovides navigation and interferometry functions in addition to typicalGPS correlator and information delivery functions.

The IMU 13 of FIG. 5 develops estimates of acceleration and attituderates along three axes. As shown in FIG. 6, the IMU 13 developsestimates along a first axis 19, a second axis 20, and a third axis 21.In practice, acceleration and attitude rates are measured alongdifferent, non-orthogonal triads of axes that are subsequentlyorthogonalized and aligned using a calibration procedure. Subsequentprocessing uses the parameters of the error model that result frominitial calibration. The error model includes bias, scale factor, noiseproperties, and various angular errors among the instrument axes,including: three non-orthogonalities for the accelerometer triad, threenon-orthogonalities for the gyroscope triad, three misalignments betweenthe accelerometer and gyroscope triads, and three misalignments to abody frame. The calibration software, optionally executed by a processor(not shown) in the IMU 13 or other processor 9 in the motioncharacterization system 6, includes a Kalman filter with the error termsas free parameters that are determined using Maximum LikelihoodParameter Estimation (MLPE) optimization or other suitable optimizationtechnique. After calibration, the IMU 13 in FIG. 5 provides calibratedacceleration and attitude rate data along three measurement axes.

FIG. 7 is a block diagram of an embodiment of the IMU 13. In oneembodiment, the IMU 13 uses three MEMS accelerometers 22 and three MEMSgyroscopes 23 for a low-cost solution. A microconverter 24 digitizesdata from the accelerometers 29 and the gyroscopes 30, accumulates setsof digitized data, and embeds synchronization data indicating a GPSepoch provided by the GPS receiver 12. The tight coupling of theinterferometry solution with the MEMS-based IMU improves the overallperformance of the motion characterization system 6.

FIG. 8 is a functional diagram of processes executed in the DSP-basedGPS receiver 12 in FIG. 5. A channel allocator 25 orchestrates the flowof data from the two RF front ends 15 (FIG. 5). Once inside the DSP, thedata is allocated to navigation correlators 26 and interferometrycorrelators 27 that are logically formed from a set of correlatorsavailable within the GPS receiver 12. The process executing in the GPSreceiver 12 configures the navigation channels to track the smallestnumber of GPS satellites that provide an acceptable navigation solutionand configures the interferometry channels to track the GPS satellitesmost nearly orthogonal to the antenna baseline and preferably low on thehorizon.

As shown in FIG. 8, the measurement processing 28 includes code rangeand carrier phase processing 29 to support navigation functions. Themeasurement processing 28 also includes interferometric processing 30 tosupport interferometry calculations. The measurement processing 28provides measurement models, linearized measurement models, errormodels, and measurement and error propagation information used bysubsequent processing.

A Kalman filter navigator 31 provides the estimation processing used tomerge the IMU and GPS measurements. Kalman filtering, which is wellknown in the art, requires a statistical mathematics model of theunderlying system dynamics and the measurement processes. The accuracyof the Kalman filter results is dependent both on the accuracy of theunderlying models and on the adherence of the models to the constraintsimposed by the Kalman filter formulation.

The measurement processing 28 and the Kalman filter navigator 31 usefundamental observables to infer system behavior. The GPS receiver 12thus uses IMU measurements, selected GPS signal observables, and aspecifically formulated Kalman filter state model to estimate attitude.

All GPS receiver 12 uses pseudorandom noise (PRN) code sequences tosynchronize the correlator channels for each tracked GPS satellite. Thiscorrelation process provides a measure of the transit time of thesignals from each GPS satellite to the user. This transit timecomputation is relatively accurate for all GPS satellites being trackedbut contains an uncertainty due to the receiver oscillator forming thebasis of the clock. Use of four GPS satellites allows solution of thethree-dimensional location of the user and the user clock error. The lowrate digital message contains information about the calibration of theGPS satellite clocks, precise orbital data for each acquired GPSsatellite, and the almanac containing less precise orbital data for allGPS satellites.

The mechanization of the GPS position solution is of little utility tothe determination of attitude. Instead, the motion characterizationsystem 6 uses two basic GPS observables for attitude measurement, whichdepend on the coherence of the transmitted GPS signal waveform. The twobasic GPS observables are:

Integrated Carrier Phase (ICP)—Because the GPS waveform is coherent, theGPS receiver can lock to the phase of the GPS satellite waveform andintegrate phase changes to arrive at a precise measure of the change inreceived carrier phase over measured time intervals. Because the GPSsatellite orbit is precisely known, the motion characterization system 6can predict the contribution to phase change resulting from Doppler. Theresidual phase change is a measure of the average velocity of the GPSreceiver during the measurement interval, a GPS epoch.

Dual-antenna carrier phase difference—For two closely spaced antennas,the carrier phase can be measured and used to infer information aboutthe range difference between the two antennas and the GPS satellite. Therange difference is ambiguous by the signal wavelength.

The ICP for a single receiver and single GPS satellite contains errorsdue to the stability of the ionosphere and uncertainty in the GPSsatellite orbit. However, by differencing the per-epoch ICP between twoclosely spaced antennas, then the resulting double differenced carrierphase measurement is free of errors from the GPS satellite orbit orionosphere. This measurement has mm-level accuracy with even low costGPS receivers.

While multiple-antenna interferometry can provide information about theattitude of the GPS baseline from single-epoch multiple-satelliteobservations, the velocity information from GPS requires a moreinferential approach. The attitude error from an IMU solution propagatesinto a velocity error in proportion to the vector cross product with thevehicle acceleration. Thus, an estimate of the attitude results bycomparing the GPS precision velocity measurement with the IMU-derivedvelocity. The motion characterization system 6 uses both attitudeinference phenomena simultaneously to provide an optimal estimate of theattitude.

The Integrated Carrier Phase observable to the jth GPS satellite at thei+1 th epoch can be described mathematically as

ICP_(j)(t _(i+1))=R _(j)(t _(i+1))−R _(j)(t _(i))+δƒ  (1)

where δƒ is the error in the receiver oscillator over the epoch. Therange is given by

$\begin{matrix}{{R_{j}( t_{i + 1} )} = \sqrt{( {{{\underset{\_}{r}}_{s_{j}}( t_{i + 1} )} - {{\underset{\_}{r}}_{u}( t_{i + 1} )}} ) \cdot ( {{{\underset{\_}{r}}_{s_{j}}( t_{i + 1} )} - {{\underset{\_}{r}}_{u}( t_{i + 1} )}} )}} & (2)\end{matrix}$

where r_(s) ^(j) is the position vector to the jth GPS satellite andr_(u) is the position vector to the receiver in a common coordinateframe. Also,

$\begin{matrix}{{R_{j}( t_{i + 1} )} = \sqrt{( {{{\underset{\_}{r}}_{s_{j}}( t_{i} )} - {{\underset{\_}{r}}_{u}( t_{i} )} + \underset{\_}{\delta \quad r}} ) \cdot ( {{{\underset{\_}{r}}_{s_{j}}( t_{i} )} - {{\underset{\_}{r}}_{u}( t_{i} )} + \underset{\_}{\delta \quad r}} )}} & (3)\end{matrix}$

where $\begin{matrix}{\underset{\_}{\delta \quad r} = {{\underset{\_}{r}\quad {\overset{\prime}{\quad Y}}_{s_{j}}\Delta \quad T} + {\int_{t_{i}}^{t_{i + 1}}{\underset{\_}{r}{\overset{\prime}{Y}}_{u}{t}}}}} & (4)\end{matrix}$

Linearizing with respect to δr yields $\begin{matrix}{{R_{j}( t_{i + 1} )} = {{R_{j}( t_{i} )} + {\frac{( {{\underset{\_}{r}}_{s_{j}} - {\underset{\_}{r}}_{u}} )}{R_{j}( t_{i} )} \cdot \underset{\_}{\delta \quad r}}}} & (5)\end{matrix}$

or $\begin{matrix}{{{R_{j}( t_{i + 1} )} = {{R_{j}( t_{i} )} + {{\underset{\_}{u}}_{j} \cdot \underset{\_}{\delta \quad r}}}},\quad {{\underset{\_}{u}}_{j} = \frac{( {{\underset{\_}{r}}_{s_{j}} - {\underset{\_}{r}}_{u}} )}{R_{j}( t_{i} )}}} & (6)\end{matrix}$

where u_(j) is the unit vector to the jth GPS satellite. Substitutingyields

ICP_(j)(t _(i+1))=u _(j) ·δr+δƒ  (7)

Equation (7) is the measurement equation relating the observable ICP tothe IMU 13 and GPS clock errors over an epoch. The term δr from equation(4) pertains to the integral of the velocity and not the instantaneousvelocity, which is important because the IMU error equation propagatesthe continuous velocity error between epochs.

Most IMU/GPS integration solutions assume the availability of acontinuous GPS velocity measure, which is derived from afrequency-lock-loop within the hardware and sampling the resultinglocked frequency. Because of the large GPS satellite-induced Doppleroffset, an accurate measurement of high instantaneous velocity requiresan extremely precise measurement of the continuous instantaneousvelocity. High-end GPS achieves velocity estimation accuracy of0.03-m/sec. The motion characterization system 6 uses the integratedvelocity rather than the instantaneous velocity to allow an order ofmagnitude accuracy improvement in performance at an order of magnitudereduction in cost.

The prior art has not used this strategy for mechanization reasons,which the Kalman filter navigator 31 of the present invention overcomes.A Kalman filter state is added for each GPS satellite according to

δrY _(j) =u _(j) ·δv  (8)

which ignores, temporarily, the coordinate frame of the measurements. Ameasurement must also be added for each GPS satellite-specific stateaccording to

Δδr _(m) =δr(t _(i+1))−δr(t _(i)).  (9)

Thus, the measurement equation (9) is a function of the differencebetween the current state and a past state. Such a Kalman filter form ishighly non-standard and results in cumbersome matrix forms. The Kalmanfilter navigator 31 supports this special case.

The dual-antenna carrier phase difference observable is the dot productof the antenna baseline (r₂ ^(b)−r₁ ^(b)) with the LOS to the jth GPSsatellite (û_(j)). Using the assumption of the GPS satellite located atinfinity leads to the following expression for the differential carrierphase (δρ):

û _(j) ^(n) ·C _(b) ^(n)(r ₂ ^(b) −r ₁ ^(b))=δρ+ρ  (10)

The unknown phase state error p accounts for phase from the twoindependent receivers. Upon filter startup, ρ is an arbitrary valuebecause of the receiver phase differences.

Equation (10) is linearized with respect to IMU-axes-to-n-frame(geodetic) misalignments, as well as for misalignments of IMU axes withrespect to the antenna baseline. By considering small geodetic angleerrors (Δθ) and antenna alignment errors (Δφ^(b)) in C_(b) ^(n), thefollowing expression results: $\begin{matrix}{{{\delta \quad \rho_{j}} - {{\underset{\_}{\hat{u}}}_{j}^{n} \cdot {{\overset{\sim}{C}}_{b}^{n}( {{\underset{\_}{r}}_{2}^{b} - {\underset{\_}{r}}_{1}^{b}} )}}} = {{{\underset{\_}{\hat{u}}}_{j}^{n} \cdot \{ {\underset{\_}{\Delta \quad \theta} \times {{\overset{\sim}{C}}_{b}^{n}( {{\underset{\_}{r}}_{2}^{b} - {\underset{\_}{r}}_{1}^{b}} )}} \}} + {{\underset{\_}{\hat{u}}}_{j}^{n} \cdot \{ {{\overset{\sim}{C}}_{b}^{n}\Delta \quad {\underset{\_}{\varphi}}^{b} \times ( {{\underset{\_}{r}}_{2}^{b} - {\underset{\_}{r}}_{1}^{b}} )} \}} + \rho}} & (11)\end{matrix}$

where {tilde over (C)}_(b) ^(n) represents the misaliged directioncosine matrix from the strapdown navigation computational process 32.

Equation (11) is the measurement equation for the Kalman filter. Theleft side of Equation (11) defines the measured-minus-predicted phasedifference. The right side of Equation (11) represents the errors inthis estimate expressed in terms of (i) IMU and antenna baselinealignment errors and (ii) receiver-to-receiver phase errors. The antennaalignment enters the equation in a similar manner as the IMU alignmentexcept that the antenna alignment is assumed constant in a body axisframe. The antenna baseline alignment error states are typicallyinitialized with standard deviations of several degrees, which isreduced during processing as the geodetic angular errors are reducedthrough the traditional transfer alignment process. Only two of thesmall angular errors for the three angles in the vector Δφ^(b) are usedsince rotation about the antenna baseline is not observable. However,the formulation keeps the three elements in the solution to allow anarbitrary antenna baseline axes orientation relative to the IMU axes 26,27, 28.

Effective system integration requires use of the IMU-to-GPS baselinemisalignment as a component of the Kalman filter. The addition of thesecond GPS antenna forms a geometric baseline. The alignment accuracy ofthe baseline relative to the IMU is directly correlated to the geodeticattitude estimation accuracy. The motion characterization system 6estimates the alignment during processing to avoid costly and non-robustinstallation measurements.

The motion characterization system 6 may optionally use a novel SigmaEtastrategy for implementing a Kalman filter from an arbitrary state vectorand measurement model. The motion characterization system 6 may also usea tailored SigmaEta Kalman filter for the dual-antenna operation,although other embodiments may use alternative forms for the Kalmanfilter. The definition of the state vector elements depends on thefollowing construct:

{dot over (g)}b=η _(gb) −gb/τ _(gb)  (12)

Equation (12) represents a first-order Markov process with white noiseinput η and correlation time τ. The subscripts associate the input andoutput noise and correlation with the specific state variable. Therepresentation of the statistical parameters allows the system error tovary in time in a statistically well-behaved manner. The clock model isa set of Brownian motion sequences, with the noise strengths derivedfrom evaluation of actual GPS receiver data.

Table 2 shows the elements of a state vector used in the Kalman filternavigator 31, where states 29-38 represent the interferometry phase. Theerror state standard deviations of these errors are initialized at about0.05 wavelengths. The ICP states are used to model the integral of theintegral of velocity along the LOS to each GPS satellite. The platformnavigation state can be highly dynamic.

TABLE 2 State Name number Dynamical Representation Velocity error 1-3δ{dot over (v)} ^(n) = δθ × C_(b) ^(n) a ^(b) + C_(b) ^(n) ab + C_(b)^(n)[asfe]a ^(b) Attitude error 4-6 δθ ^(Ý) = C_(b) ^(n)[(gb + [gsfe]ω_(b/i) ^(b))x] Position error 7-9 δ{dot over (r)} ^(t) = C_(n) ^(t) v^(n) Accelerometer 10-12 α{dot over (Y)}b = η _(ab) − ab/τ_(ab) biasGyroscope bias 13-15 {dot over (g)}b = η _(gb) − gb/τ_(gb) Accelerometer16-18 a{dot over (s)}fe = η _(asfe) − asfe/τ_(asfe) scale factor errorGyroscope scale 19-21 g{dot over (s)}fe = η _(gsfe) − gsfe/τ_(gsfe)factor error IMU-GPS latency 22 {dot over (T)}_(l) = η_(T) − T_(l)/τ_(T)GPS clock 23-25 {dot over (β)} = η_(β;) {dot over (f)} = β + η_(f); {dotover (c)} = f + η_(c) Baseline 26-28 {dot over (φ)} = 0 alignmentInterferometry 29-38 {dot over (Ω)} = η_(Ω) − Ω/τ_(Ω) phase ICP states39-48 Δ{dot over (r)}_(j) = C_(n) ^(t) u _(j) ^(n) · v ^(n)

The Kalman filter navigator 31 avoids the situation where measurementsare combinations of current and past state values by doing a reset onthe ICP states at each epoch. The state values are set to zero, and thestandard deviations are set to very near zero. The Kalman filternavigator 31 also sets the state correlation coefficients to zero alongthe rows and columns associated with the reset state. This processresults in a very simple implementation with the expense of addingauxiliary states and managing the reset process.

The measurement formulation for the dual-antenna Kalman filter includesthree sets of measurements corresponding to the coarse positionestimates, the code tracking process, the ICP measurements, and thedual-antenna measurements.

With two GPS receivers each tracking all GPS satellites in view, theKalman filter used by the Kalman filter navigator 31 allows up to 30measurements per epoch, which correspond to ten measurements for eachmeasurement set. Each measurement is processed individually using theKalman filter update formulation.

The Kalman filter allows recursive processing of the measurement data,which allows the sequential processing of measurements. However, for theprocessing to provide accurate results according to the practiced art,each measurement must be uncorrelated with the prior sequentialmeasurement. For interferometry, processing typically differencesintegrated carrier phase measurements, first between antennas and thenbetween GPS satellites to obtain a double difference measurement.

Carrier phase differencing between closely spaced antennas for a commonGPS satellite removes common-mode errors associated with the ionospherepath length and GPS satellite transmission. However, a common-modereceiver clock error remains following the differencing. Often, in thepracticed art, the processing performs a second difference betweensignals from two GPS satellites to remove the common time bias in thecommon mode clock error. The sequential measurements now becomecorrelated if they include noise associated with a common GPS satellite.For example, if z_(A)=M_(B)−M_(A) and z_(B)=M_(C)−M_(A) representmeasurement differences between satellite B and satellite A andsatellite C and satellite A, respectively, then the measurements z_(A)and z_(B) are correlated because each measurement difference containsthe same noise from M_(A). Consequently, the correlations in theresulting double differenced measurements cannot be processed directlyby a straightforward Kalman filter formulation. The single-differencedmeasurements do not contain correlations; however, the Kalman filterstate vector dynamic modeling procedure must model the common-mode clockerrors. The Kalman filter navigator 31 uses the single-differencecarrier phase measurement model with CPU clock error model, and thedouble differenced carrier phase measurement may be used in alternativeembodiments.

Multipath interference in a GPS receiver results from receiving thecombination of the direct path and reflected path from a single GPSsatellite. The extraneous reflections occur from fixed structures in thesurroundings, such as buildings and towers, from terrain features withinthe surrounding environment, or from the portion of the platformstructure. In an urban environment in the proximity of tall buildings,multipath will result in pseudorange errors of 5-10 meters for affectedGPS satellites. In such situations, phase multipath can produceinterferometric solutions that are significantly in error. The motioncharacterization system 6 uses strategies for multipath mitigation thatinclude detecting and discarding GPS satellites with evidence ofmultipath, using closely spaced antennas, and having a carrier trackingloop that uses platform acceleration aiding. The strategies formultipath mitigation include:

Deep signal fades can occur with the phased addition of all signalreturns, resulting in loss of lock. Anomalous tracking conditions canoccur before the loss of lock and during re-acquisition. Because of theability to selectively depend on the IMU navigation solution, the motioncharacterization system 6 can operate with fewer, possibly zero, GPSsatellites for an extended period. Additionally, the motioncharacterization system 6 is capable of quickly discarding navigationdata from GPS satellites that are providing motion estimates notconsistent with measured accelerations or other GPS satellitemeasurements.

GPS antenna design, the design of antenna ground planes, and care inplacing the GPS antenna on a platform offer some multipath protection;however, multipath signals are often present in any complex urban sceneor vehicle mounting surface. For path lengths that differ considerably,as in the case for reflections from nearby buildings, GPS signaltracking methods involving narrow correlator bandpass methods canprovide multipath protection on each receiver channel. However, becauseinterferometry relies on mm-level position differences, multipathreflections with even small path length differences appear differentlyat the two GPS antennas and can pose serious problems. As the twoantennas are brought closer together in the presence of a complexmultipath environment, both antennas are more likely to see the samereflected energy pattern. Therefore, the close spacing of the navigationantennas 7 used by the motion characterization system 6 mitigatesmultipath.

The individual channels of the correlator chips 26 and 27 provide bothpseudorandom noise (PRN) code tracking and carrier tracking for each GPSsatellite. Typically, the expected dynamics of the vehicle along theline-of-sight (LOS) to the GPS satellite is the single most significantaspect of the tracking loop designs. By aiding the tracking loops withacceleration along the LOS, the motion characterization system 6 cananticipate the platform dynamics, thus enabling faster acquisition, lesssensitivity to spurious emissions, and greater robustness to multipathand vehicle dynamics. The motion characterization system 6 optionallydetermines acceleration aiding estimates using range-rate prediction toeach carrier track loop along with adjustments to code and carrier trackloop bandwidths and PRN code dither values. Acceleration aiding requiresboth measurement of the vehicle acceleration vector as well as knowledgeof the geodetic orientation of the vehicle. The motion characterizationsystem 6 may use parameterized tracking loops configured to mediatemultipath.

The measurement processing 28 in the GPS satellite selection controlcompares the GPS signals for GPS satellites tracked at both antennas.For non-multipath conditions, carrier/code loop processing for eachchannel should be identical. For identical antennas andantenna-to-receiver signal paths, the only source of difference comesfrom on-platform multipath. Fortunately, redundant GPS satellites arelikely to exist for both navigation and interferometry purposes. A landnavigation system can perform well with only three GPS satellites inview and the integration with the IMU allows the three GPS satellites tobe used sequentially rather than simultaneously.

Broadband satellite data links use Ka band frequencies to achieveGHz-wide data bandwidth. At these higher frequencies, radio frequency(RF) energy is more highly focused for a given antenna size, and antennagain can be made very high along a preferred direction. The highdirectionality of Ka band transmission provides a natural immunity tointerference and signal leakage and the high-gain antennas can bemanufactured in compact sizes. However, Ka band communication suffersfrom higher atmospheric attenuation, and the narrow beamwidth 33 in FIG.9 of the communicating antennas demands more attention to pointing thebeam at the communication source.

Selecting an approach to pointing a receiving antenna at a broadbandsatellite source depends on the dynamics of the relative geometry.Considering the satellite source, the pointing solution depends onwhether the antenna is pointed at an earth-fixed source, as in the caseof a Geosynchronous Earth Orbit (GEO) Satellite, or at a source movingrelative to the earth, as in the case of a Low Earth Orbit (LEO)satellite. Considering the receiver antenna, the pointing solution alsodepends on whether the antenna is mounted on a rigid platform, such asthe top of a building, or on a dynamically moving platform, such as thetop of an automobile or an aircraft. There are also intermediatecircumstances where the platform may be slightly moving, such as on atower, or occasionally transported, as in an emergency situation.

For even the least stressful pointing scenario, a building top with GEOsatellite, the very narrow antenna beam must be precisely pointed.Manual setup requires both precision mechanical alignment andrealignment in the event the equipment is jarred, buffeted by winds, ormoved by vibrations. By achieving in a low cost solution the errorbudget specified for the most stressful pointing applications, which isthe moving vehicle with a LEO satellite network, the present inventionpermits a low cost solution having application to all broadband pointingsituations.

For communication from a moving vehicle as in FIG. 1, the pointingsystem deflects the antenna with respect to the vehicle to maintain theproper pointing direction to the content-delivery satellite. Deflectingthe beam can be accomplished using electrical techniques, mechanicaltechniques, or a combination of electrical and mechanical techniques.For an antenna having a fixed size as shown in FIG. 9, the presentinvention provides a pointing technique that keeps the antenna mainbeam33 pointed at a content-delivery satellite.

A detailed simulation of the invention models the GPS satelliteconstellation, vehicle motion, INS hardware, GPS receiver, and theprocessing performed by the motion characterization system 6 todemonstrate the value of augmenting transfer alignment with GPSinterferometry. Table 3 includes simulation parameters and correspondingnominal values. Results from the simulations, which are not shown, usingthe simulation parameters of Table 3 illustrate the operation oftransfer alignment without interferometry on a slow-moving groundvehicle, showing the sensitivity to vehicle motion and the reliance onhigh-quality gyroscope measurements. By adding one GPS antenna tosupport interferometric measurements, the results of the simulation showthe elimination of the drawbacks of transfer alignment.

TABLE 3 Simulation Parameter Nominal Value antenna baseline distance 12in baseline alignment sigma 1 mrad interferometric phase bias sigma 2 mminterferometric phase sigma 1 mm gyroscope bias sigma 500 deg/hrgyroscope scale factor error sigma 20000 PPM gyroscope noise 2.56deg/root-hr accelerometer bias sigma 10 mG accelerometer scale factorerror 20000 PPM sigma 0.4 m/s/root- hr accelerometer noise 200 secgyroscope error correlation time 200 sec acceleration error correlationtime 10 mm delta pseudorange error sigma 0.1 m pseudorange error sigma 8m GPS clock bias sigma 0.1 m/sec GPS clock oscillator bias sigma 10 mIMU lever arm to master GPS 0 m Speed 5 mph

All the problems associated with transfer alignment stem from theinability to sense yaw attitude directly. Transfer alignment requireschanges in vehicle velocity to enable estimation of yaw from velocitymatching and requires precision gyroscopes because of the algorithmicneed for heavy smoothing of the platform motion. The motioncharacterization system 6 overcomes this dilemma by sensing the yawattitude from a completely different source—dual-antenna interferometry.As discussed above the approach for sensing yaw attitude requires onlytwo antennas because transfer alignment provides precision estimates ofroll and pitch. In addition, the solution for sensing yaw attitudeprovided by the present invention is relatively insensitive to GPSantenna spacing because of the smoothing benefits of even low-accuracyinertial components. The tight coupling of the interferometry solutionwith the IMU makes sensing yaw attitude in a low cost solution possible.

The vehicle trajectory used for the simulation has a changing vehiclevelocity profile that transfer alignment requires for good performance.By using a changing velocity profile, the simulation provides acomparatively conservative view of the benefit of the invention. Thesimulation uses values for the nominal IMU parameters that arerepresentative of automotive-grade MEMS accelerometers and gyroscopes.The MEMS gyroscope is 500-times poorer in bias and over 100 times poorerin noise figure than the typical tactical gyroscope. The MEMSaccelerometer is only slightly poorer than the current tacticalaccelerometer. The GPS measurement quality is typical of commercialquality, low-cost units, and the error characteristics for the GPSinterferometry configuration reflects practical installationconstraints. The simulation uses a 1 mph nominal platform velocity toillustrate the performance of the motion characterization system 6 withonly slight platform motion.

The simulation results shown in FIG. 10 indicate that smallinterferometry baselines provide good yaw estimation accuracy. Forexample, a 12-in GPS antenna separation together with a nominal 1-mmphase error provides a yaw estimation accuracy of 1.7-mrad (0.1-deg).The 1-mm phase error over a 12-in antenna separation results in asingle-look angular accuracy of 3-mrad. The use of multiple GPSsatellites and the smoothing effects of the gyroscope measurementsfurther improve accuracy.

The simulation results shown in FIG. 11 indicate that accurate estimatesof yaw are relatively insensitive to gyroscope accuracy over the modeledregion. In addition, although not shown, the roll and pitch estimationaccuracy remains excellent. The interferometry is the dominant factor inyaw angle observability and not the smoothing that results from ratemeasurement. Additional simulation results are shown and described inU.S. Provisional Application No. 60/272,170, filed on Feb. 28, 2001; theentire teachings of which are incorporated herein by reference.

Traditional GPS-alone interferometry solutions require an initializationstep using sophisticated search procedures to overcome thethree-dimensional wavelength ambiguity associated with the differentialrange measurement. Transfer alignment provides an initial yaw estimatewith vehicle motion; otherwise, an eight-position search of the 0-360deg yaw space will be required. The dual-antenna solution employed bythe motion characterization system 6 mitigates initialization byrequiring ambiguity resolution over only a single axis of yaw. Theexcellent pitch and roll estimate provided by the accelerometersprovides improved performance over a conventional GPS-aloneinterferometry system. In addition, in one embodiment, a short 12-inbaseline of the antennas 7 significantly reduces sensitivity to yawuncertainty because the ambiguity is on the same order as the baselinelength. Thus, only a very coarse estimate of yaw, about 45 deg, ensuresan unambiguous attitude solution.

FIG. 12 is a diagram of an example of a broadband communication system50 with integrated pointing control according to the principles of thepresent invention. An example shown in FIG. 12 of the broadbandcommunication system 50 integrates an broadband antenna system 47, acommunications receiver and transmitter 34, a pointing controller 43,The broadband antenna system 47 consists of communications antenna array49 and one embodiment of the motion measurement system 6 mounted on oneor more substrates, which includes 2 GPS antennas, an InertialMeasurement Unit, an interferometric GPS receiver, and a processor.

The communications receiver and transmitter 34 may be constructed from acommodity chipset, applications specific chipsets, or discretecomponents. The broadband communications system 50 may include thecommunications functions typically found in a commercially availablecommunications receiver and transmitter. For the receive chain, thefunctions include downconversion and gain control 35, analog-to-digitalconversion 36, tuning and filtering 37, and demodulation and decoding38. For the transmit chain, the functions include encoding andmodulation 39, synthesis and filtering 40, digital-to-analog conversion41, and upconversion 42.

The pointing controller 43 uses the capabilities of the presentinvention as described above and adds the processing necessary toeffectively point the communications antenna array 49 at a transmittingsource or receiving sink. The pointing controller 43 includes RFprocessing 44, GPS processing 45, and filtering and data processing 46.Many other integration methods of the example broadband communicationsystem 50 are possible, as determined by cost and application.

While this invention has been particularly shown and described withreferences to preferred embodiments thereof, it will be understood bythose skilled in the art that various changes in form and details may bemade therein without departing from the scope of the inventionencompassed by the appended claims.

What is claimed is:
 1. A motion characterization system, comprising: twoantennas, mounted to a rigid body, to receive navigation signals; acollection of motion sensing devices, including rate gyroscopesproviding poorer than ten degrees per hour accuracy, mounted on therigid body to provide electrical signals providing motion information;and a processor electrically coupled to process electrical signals fromthe antennas and the motion sensing devices to provide an attitudemeasurement of the rigid body under arbitrary motion conditions.
 2. Themeasurement system as claimed in claim 1, wherein the antennas areseparated by less than three wavelengths of a signal received from anexternal signaling source.
 3. The measurement system as claimed in claim2, wherein the external signaling source is a plurality of GPSsatellites.
 4. The measurement system as claimed in claim 3, wherein theantennas are separated by about 150 millimeters (mm).
 5. The measurementsystem as claimed in claim 1, wherein the motion sensing devices includeat least one MEMS device.
 6. The measurement system as claimed in claim5, wherein the processor processing the motion sensing devices providesan acceleration signal.
 7. The measurement system as claimed in claim 1,wherein the arbitrary motion conditions include general moving motions,constant velocity motions, and stationary motions.
 8. The measurementsystem as claimed in claim 1, wherein the attitude measurement isaccurate to within about 1 degree.
 9. The measurement system as claimedin claim 1, wherein one antenna is used supports navigation processingand the other antenna supports interferometry processing.
 10. Themeasurement system as claimed in claim 1, wherein alignment errorbetween the antenna baseline and the motion sensing devices is estimatedby software.
 11. The measurement system as claimed in claim 1, whereinthe processor includes a twelve-channel GPS receiver.
 12. Themeasurement system as claimed in claim 11, wherein after aninitialization process, unused channels in the GPS receiver (i) receivedata by one of the antennas supporting interferometry, and (ii) trackGPS satellites most nearly orthogonal to the antenna baseline.
 13. Amethod for determining attitude of a rigid body, comprising: receivingnavigation signals at the rigid body; measuring motion of the rigidbody, including rate with poorer than ten degrees per hour accuracy, andproviding corresponding motion signals; and processing the navigationsignals and motion signals to provide an attitude measurement of therigid body under arbitrary motion conditions.
 14. The method as claimedin claim 13, wherein the navigation signals are GPS signals.
 15. Themethod as claimed in claim 13, wherein the arbitrary motion conditionsinclude general moving motions, constant velocity motions, andstationary motions.
 16. A motion characterization system, comprising:platform means; means for receiving navigation signals at said platformmeans; means for sensing motion of said platform means and for providingassociated motion signals, including rate of said platform means with anaccuracy of poorer than ten degrees per hour; and means for processingthe navigation signals and the motion signals to provide an attitudemeasurement of said platform means under arbitrary motion conditions.17. A mobile system, comprising: a platform; a motion characterizationsystem including: (i) a first navigation antenna and second navigationantenna coupled to the platform to receive navigation carrier signals,(ii) a plurality of motion sensing devices coupled to the platform toprovide motion signals representative of motion of the platform, and(iii) a processor (a) coupled to the antennas to make range and carrierphase measurements of the navigation carrier signals at a plurality ofepochs defining the navigation carrier signals and to segment the rangeand carrier phase measurements for the navigation carrier signals into anavigation set and an interferometry set, the sets having at least onenavigation carrier signal for a plurality of navigation epochs andsupporting interferometry calculations and (b) coupled to the motionsensing devices to receive the motion signals and to convert the motionsignals into measurements of platform motion for a plurality of epochsdefined for the motion signals, the processor determining a navigationsolution including position and attitude of the platform from the rangeand carrier phase measurements for the navigation carrier signals andfrom measurements of platform motion developed from the motion signals;and a subsystem in communication with the motion characterization systemresponsive to the navigation solution.
 18. The mobile system as claimedin claim 17, wherein the motion sensing devices include rate gyroscopesproviding poorer than ten degrees per hour accuracy.
 19. The mobilesystem as claimed in claim 17, wherein the first and second navigationantennas are separated by less than three wavelengths of the navigationcarrier signal.
 20. The mobile system as claimed in claim 17, whereinthe navigation carrier signals are provided by a plurality of GPSsatellites.
 21. The mobile system as claimed in claim 17, wherein themotion sensing devices include at least one MEMS device.
 22. The mobilesystem as claimed in claim 17, wherein the platform motion includesgeneral moving motions, constant velocity motions, and stationarymotions.
 23. The mobile system as claimed in claim 17, wherein theattitude measurements are accurate to within about 1 degree.
 24. Themobile system as claimed in claim 17, wherein the first navigationantenna supports navigation processing and the other antenna supportsinterferometry processing.
 25. The mobile system as claimed in claim 17,wherein software executed by the processor corrects for alignment errorbetween a baseline defined by the first and second navigation antennasand a coordinate system defined by the motion sensing devices.
 26. Themobile system as claimed in claim 17, wherein the processor includes atwelve-channel GPS receiver.
 27. The mobile system as claimed in claim26, wherein, after an initialization process, unused channels in the GPSreceiver (i) receive data from the second navigation antenna, acting asan interferometry antenna, and (ii) track GPS satellites most nearlyorthogonal to a baseline defined by the first and second navigationantennas.
 28. The mobile system as claimed in claim 17, wherein theprocessor allocates, in an optimized manner, a plurality of navigationsignals to the navigation set or the interferometry set using navigationand interferometry performance estimates.
 29. The mobile system asclaimed in claim 17, wherein the processor improves the accuracy of therange, carrier phase, and interferometry processing for the navigationcarrier signals by providing estimates of acceleration along aline-of-sight from the platform to each of a plurality of navigationsignal sources.
 30. The mobile system as claimed in claim 17, whereinthe processor synchronizes the measurements of platform motion, providedby the motion sensing devices, using time estimates developed from thenavigation carrier signals.
 31. The mobile system as claimed in claim17, wherein the subsystem includes a directive antenna directing anassociated antenna beam via mechanical means.
 32. The mobile system asclaimed in claim 17, wherein the subsystem includes a directive antennadirecting an associated antenna beam via electronic means.
 33. Themobile system as claimed in claim 17, wherein the subsystem includes adirective antenna mechanically coupled to the platform and electricallycoupled to the motion characterization system to direct an associatedantenna beam in response to the navigation solution.
 34. The mobilesystem as claimed in claim 17, wherein the subsystem includes a vehiclesafety system.
 35. A method for determining attitude of a stationary ormoving platform, comprising: receiving navigation carrier signals;making range and carrier phase measurements of the navigation carriersignals at a plurality of navigation system epochs defining thenavigation carrier signals; segmenting the range and carrier phasemeasurements for the navigation carrier signals into a navigation setand an interferometry set, the sets (i) having at least one navigationcarrier signal for a plurality of the navigation system epochs and (ii)supporting interferometry calculations; receiving motion signalsrepresenting motion of the platform; converting the motion signals intomeasurements of platform motion for a plurality of epochs defined forthe motion signals; and determining a navigation solution includingposition and attitude of the platform from the range and carrier phasemeasurements for the navigation carrier signals and from themeasurements of platform motion developed from the motion signals. 36.The method according to claim 35, further including allocating, in anoptimizing manner, a plurality of navigation carrier signals to thenavigation set or the interferometry set using navigation andinterferometry performance estimates.
 37. The method according to claim35, further including improving the accuracy of the range, carrierphase, and interferometry processing for the navigation carrier signalsby providing estimates of the acceleration along the line-of-sight fromthe platform to each of a plurality of navigation system signal sources.38. The method according to claim 35, further including synchronizingthe measurements of vehicle motion, provided by the motion sensingdevices, using the time estimates developed from the navigation carriersignals.
 39. The method according to claim 35, wherein the navigationcarrier signals are received by two navigation system antennas that aremounted to the platform and the motion signals are provided by motionsensing devices also mounted to the platform.
 40. The method accordingto claim 35, wherein the navigation set is associated with one of thetwo navigation system antennas and the interferometry set is associatedwith the other of the two navigation system antennas.
 41. The methodaccording to claim 35, to further include providing the navigationsolution for use by a subsystem associated with the platform.
 42. Themethod according to claim 35, wherein the subsystem is a safety system,stability control system, pointing system, geodetic position controlsystem, attitude control system, or mapping projection system.
 43. Themethod according to claim 35, wherein the navigation carrier signals areprovided by a plurality of GPS satellites.
 44. An apparatus fordetermining attitude of a platform under arbitrary motion conditions,comprising: means for receiving navigation carrier signals; means formaking range and carrier phase measurements of the navigation carriersignals at a plurality of epochs defining the navigation carriersignals; means for segmenting the range and carrier phase measurementsfor the navigation carrier signals into a navigation set and aninterferometry set, the sets (i) having at least one navigation carriersignal for a plurality of navigation system epochs and (ii) supportinginterferometry calculations; means for converting the motion signalsinto measurement of platform motion for a plurality of navigation systemepochs defined for the motion signals; and means for determining anavigation solution including position and attitude of the platform fromthe range and carrier phase measurements of platform motion developedfrom the motion signals.